Eye lens radiation exposure in paediatric interventional treatment of retinoblastoma.

Retinoblastoma represents 3% of cancers in children under fifteen years of age. The standard paediatric treatment for saving the affected eye is supraselective intra-arterial chemotherapy performed in interventional rooms. In order to address the radiation toxicity due to the angiography, the aim of this study was to determine the typical dose value corresponding to the procedure, estimate the paediatric patients' eye lens dose and study the relationship between dose indicators and dose to the lens. An automatic dose management software was installed in two interventional rooms to obtain the distribution of the dose indicators kerma-area product and reference-point air kerma, getting a typical value 16 Gy·cm2 and 130 mGy, respectively (n = 35). The eye lens dose estimates were obtained with photoluminescent dosimeters placed on the patient's eyelids. In the left eye, the entrance surface air kerma was 44.23 ± 2.66 mGy, and 12.72 ± 0.89 mGy in the right eye (n = 10). There was a positive correlation between dose to the lens per procedure and dose indicators, with R2 > 0.65 for both eyes. Based on this information, the threshold for the onset of radiation-induce cataracts (500 mGy) will be exceeded if the treatment is performed for more than 8 sessions.

Eye lens dose levels in interventional rooms using simple phantom simulation, dose management software and Monte Carlo method of uncertainty assessment.

This paper presents a fast method to estimate the annual eye lens dose levels for interventional practitioners applying the Monte Carlo method of uncertainty assessment. The estimation was performed by placing an anthropomorphic phantom in the typical working position, and applying the habitually employed protocol. No radiation protection devices were considered in the simulation. The results were compatible with the measurements performed during interventions by placing dosimeters in the vicinity of the eyes of two paediatric interventional cardiologists working with a fluoroscopic biplane system.

Caracterización y simulación de ruido en las imágenes de PET reconstruidas con OSEM: desarrollo de un método para la generación de imágenes sintéticas / Characterization and simulation of noise in PET images reconstructed with OSEM: Development of a method for the generation of synthetic images

Introducción: Los objetivos del trabajo son caracterizar las propiedades de la imagen 2D PET reconstruida mediante el algoritmo ordered-subset expectation maximization (OSEM) y proponer un nuevo método de generación de imágenes sintéticas. Material y métodos: El ruido se analiza en términos de magnitud, correlación espacial y distribución espectral a través de la desviación estándar, la función de autocorrelación y el espectro de potencias de ruido (NPS, por noise power spectrum), respectivamente. También se estudian sus variaciones con la posición y la cantidad de actividad. Este análisis del ruido se realiza sobre imágenes de maniquí a partir de distribuciones de actividad de 18F homogéneas. Para estudiar la resolución espacial del sistema a través de la point spread function (PSF) se emplean los coeficientes de recuperación medidos en esferas calientes en diferentes entornos radiactivos. Las funciones PSF y NPS proporcionan la base del método de simulación propuesto: convolución con la PSF como núcleo y adición de ruido a partir del NPS. Resultados: El análisis del ruido espectral muestra que la principal contribución es de naturaleza aleatoria. También se observa que la corrección de atenuación no altera la textura del ruido pero sí modifica su magnitud. Finalmente, las imágenes sintéticas de 2 maniquíes, uno de ellos un cerebro anatómico, son comparadas cuantitativamente con las imágenes experimentales, encontrando un buen acuerdo en términos de valores de píxel y correlaciones entre píxeles. Así, la razón contraste-ruido para la esfera más grande del maniquí NEMA IEC es 10,7 en la imagen sintética y 8,8 en la imagen experimental. Conclusiones: Las propiedades de las imágenes PET-OSEM pueden ser descritas por las funciones NPS y PSF. Las imágenes simuladas, incluyendo regiones anatómicas, son generadas satisfactoriamente mediante el método propuesto basado en las funciones NPS y PSF

Introduction: The goals of the study are to characterize imaging properties in 2D PET images reconstructed with the iterative algorithm ordered-subset expectation maximization (OSEM) and to propose a new method for the generation of synthetic images. Material and methods: The noise is analyzed in terms of its magnitude, spatial correlation, and spectral distribution through standard deviation, autocorrelation function, and noise power spectrum (NPS), respectively. Their variations with position and activity level are also analyzed. This noise analysis is based on phantom images acquired from 18F uniform distributions. Experimental recovery coefficients of hot spheres in different backgrounds are employed to study the spatial resolution of the system through point spread function (PSF). The NPS and PSF functions provide the baseline for the proposed simulation method: convolution with PSF as kernel and noise addition from NPS. Results: The noise spectral analysis shows that the main contribution is of random nature. It is also proven that attenuation correction does not alter noise texture but it modifies its magnitude. Finally, synthetic images of 2 phantoms, one of them an anatomical brain, are quantitatively compared with experimental images showing a good agreement in terms of pixel values and pixel correlations. Thus, the contrast to noise ratio for the biggest sphere in the NEMA IEC phantom is 10.7 for the synthetic image and 8.8 for the experimental image. Conclusions: The properties of the analyzed OSEM-PET images can be described by NPS and PSF functions. Synthetic images, even anatomical ones, are successfully generated by the proposed method based on the NPS and PSF

Characterization and simulation of noise in PET images reconstructed with OSEM: Development of a method for the generation of synthetic images. / Caracterización y simulación de ruido en las imágenes de PET reconstruidas con OSEM: desarrollo de un método para la generación de imágenes sintéticas.

INTRODUCTION: The goals of the study are to characterize imaging properties in 2D PET images reconstructed with the iterative algorithm ordered-subset expectation maximization (OSEM) and to propose a new method for the generation of synthetic images. MATERIAL AND METHODS: The noise is analyzed in terms of its magnitude, spatial correlation, and spectral distribution through standard deviation, autocorrelation function, and noise power spectrum (NPS), respectively. Their variations with position and activity level are also analyzed. This noise analysis is based on phantom images acquired from 18F uniform distributions. Experimental recovery coefficients of hot spheres in different backgrounds are employed to study the spatial resolution of the system through point spread function (PSF). The NPS and PSF functions provide the baseline for the proposed simulation method: convolution with PSF as kernel and noise addition from NPS. RESULTS: The noise spectral analysis shows that the main contribution is of random nature. It is also proven that attenuation correction does not alter noise texture but it modifies its magnitude. Finally, synthetic images of 2 phantoms, one of them an anatomical brain, are quantitatively compared with experimental images showing a good agreement in terms of pixel values and pixel correlations. Thus, the contrast to noise ratio for the biggest sphere in the NEMA IEC phantom is 10.7 for the synthetic image and 8.8 for the experimental image. CONCLUSIONS: The properties of the analyzed OSEM-PET images can be described by NPS and PSF functions. Synthetic images, even anatomical ones, are successfully generated by the proposed method based on the NPS and PSF.

Radiation dose optimisation for conventional imaging in infants and newborns using automatic dose management software: an application of the new 2013/59 EURATOM directive.

Objective: The new 2013/59 EURATOM Directive (ED) demands dosimetric optimisation procedures without undue delay. The aim of this study was to optimise paediatric conventional radiology examinations applying the ED without compromising the clinical diagnosis. METHODS: Automatic dose management software (ADMS) was used to analyse 2678 studies of children from birth to 5 years of age, obtaining local diagnostic reference levels (DRLs) in terms of entrance surface air kerma. Given local DRL for infants and chest examinations exceeded the European Commission (EC) DRL, an optimisation was performed decreasing the kVp and applying the automatic control exposure. To assess the image quality, an analysis of high-contrast resolution (HCSR), signal-to-noise ratio (SNR) and figure of merit (FOM) was performed, as well as a blind test based on the generalised estimating equations method. RESULTS: For newborns and chest examinations, the local DRL exceeded the EC DRL by 113%. After the optimisation, a reduction of 54% was obtained. No significant differences were found in the image quality blind test. A decrease in SNR (-37%) and HCSR (-68%), and an increase in FOM (42%), was observed. CONCLUSION: ADMS allows the fast calculation of local DRLs and the performance of optimisation procedures in babies without delay. However, physical and clinical analyses of image quality remain to be needed to ensure the diagnostic integrity after the optimisation process. Advances in knowledge: ADMS are useful to detect radiation protection problems and to perform optimisation procedures in paediatric conventional imaging without undue delay, as ED requires.

Segmentación de volúmenes tumorales en imágenes PET mediante un método iterativo basado en valor umbral / Target volume segmentation of PET images by an iterative method based on threshold value

Objetivos. Se presenta un método de segmentación automático para imágenes de tomografía por emisión de positrones (PET) basado en una aproximación iterativa mediante valor umbral, que incluye la influencia tanto del tamaño de la lesión como del fondo presente durante la adquisición. Material y métodos. A partir de un estudio de imagen PET de un maniquí que contiene esferas de diversos tamaños y en diferentes entornos radiactivos conocidos, se determinan los valores umbral óptimos que suponen una correcta segmentación de volúmenes. Estos valores óptimos son normalizados al fondo y ajustados, mediante técnicas de regresión, a una función de 2 variables: volumen de la lesión y relación señal-fondo (RSF). Esta función de ajuste es usada para construir un método de segmentación iterativo, y, basándose en él, se propone un procedimiento de contorneo automático. Se valida dicho procedimiento sobre estudios en maniquí y se comprueba su viabilidad aplicándose, de manera retrospectiva, sobre 2 pacientes oncológicos. Resultados. La función de ajuste obtenida presenta una dependencia lineal con la RSF e inversamente proporcional y negativa con el volumen. Durante la validación del método iterativo propuesto se encuentra que las desviaciones de volumen respecto al valor real y al volumen TC están por debajo del 10 y del 9%, respectivamente, excepto para lesiones con un volumen por debajo de 0,6 ml. Conclusiones. El método automático de segmentación propuesto puede ser aplicado en la práctica clínica para la planificación de tratamientos de lesiones tumorales en radioterapia de manera sencilla y fiable con una precisión cercana a la resolución de la imagen PET (AU)

Objectives. An automatic segmentation method is presented for PET images based on an iterative approximation by threshold value that includes the influence of both lesion size and background present during the acquisition. Material and methods. Optimal threshold values that represent a correct segmentation of volumes were determined based on a PET phantom study that contained different sizes spheres and different known radiation environments. These optimal values were normalized to background and adjusted by regression techniques to a two-variable function: lesion volume and signal-to-background ratio (SBR). This adjustment function was used to build an iterative segmentation method and then, based in this mention, a procedure of automatic delineation was proposed. This procedure was validated on phantom images and its viability was confirmed by retrospectively applying it on two oncology patients. Results. The resulting adjustment function obtained had a linear dependence with the SBR and was inversely proportional and negative with the volume. During the validation of the proposed method, it was found that the volume deviations respect to its real value and CT volume were below 10% and 9%, respectively, except for lesions with a volume below 0.6 ml. Conclusions. The automatic segmentation method proposed can be applied in clinical practice to tumor radiotherapy treatment planning in a simple and reliable way with a precision close to the resolution of PET images (AU)

[Target volume segmentation of PET images by an iterative method based on threshold value]. / Segmentación de volúmenes tumorales en imágenes PET mediante un método iterativo basado en valor umbral.

OBJECTIVES: An automatic segmentation method is presented for PET images based on an iterative approximation by threshold value that includes the influence of both lesion size and background present during the acquisition. MATERIAL AND METHODS: Optimal threshold values that represent a correct segmentation of volumes were determined based on a PET phantom study that contained different sizes spheres and different known radiation environments. These optimal values were normalized to background and adjusted by regression techniques to a two-variable function: lesion volume and signal-to-background ratio (SBR). This adjustment function was used to build an iterative segmentation method and then, based in this mention, a procedure of automatic delineation was proposed. This procedure was validated on phantom images and its viability was confirmed by retrospectively applying it on two oncology patients. RESULTS: The resulting adjustment function obtained had a linear dependence with the SBR and was inversely proportional and negative with the volume. During the validation of the proposed method, it was found that the volume deviations respect to its real value and CT volume were below 10% and 9%, respectively, except for lesions with a volume below 0.6 ml. CONCLUSIONS: The automatic segmentation method proposed can be applied in clinical practice to tumor radiotherapy treatment planning in a simple and reliable way with a precision close to the resolution of PET images.

Energy deposition by a 106Ru/106Rh eye applicator simulated using LEPTS, a low-energy particle track simulation.

The present study introduces LEPTS, an event-by-event Monte Carlo programme, for simulating an ophthalmic (106)Ru/(106)Rh applicator relevant in brachytherapy of ocular tumours. The distinctive characteristics of this code are the underlying radiation-matter interaction models that distinguish elastic and several kinds of inelastic collisions, as well as the use of mostly experimental input data. Special emphasis is placed on the treatment of low-energy electrons for generally being responsible for the deposition of a large portion of the total energy imparted to matter.